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International educational migration as a “soft power resource” in the globalization era

2020· article· en· W3000930588 on OpenAlex
Vera A. Suvorova, И.А. Бронников

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUPRAVLENIE / MANAGEMENT (Russia) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCentral Asia Education and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsCommonwealthMinistry of Foreign AffairsSoft powerPolitical sciencePopularityRussian federationAgency (philosophy)GlobalizationState (computer science)Power (physics)Christian ministryInternational educationHigher educationChinaEconomic growthPublic administrationSociologySocial scienceRegional scienceLaw

Abstract

fetched live from OpenAlex

The international educational migration as a resource of «soft power» of the state has been analyzed in the article. Based on comprehensive analysis of the existing definitions of educational migration the author’s interpretation of this concept have been proposed. Based on the data of UNESCO, the Institute of international education of the United States, the Ministry of Science and Higher Education of the Russian Federation the statistics of international educational migration has been presented and analyzed. The main emphasis has been made on such categories of international educational migrants as students (bachelors, masters), postgraduate students. The reasons for the popularity of foreign students in countries such as Canada and the United States have been described. Based on the study two groups of factors have been highlighted: external and internal (motivational) factors, influencing decision-making in choosing the country of study. Based on the data of the Ministry of Science and Higher Education of the Russian Federation, the advantages of education in Russia have been analyzed. The issue of adaptation of foreign students in Russian universities has been considered: first-year curatorial programs, the Institute of student fellowships. It has been concluded hat Russian universities have a wealth of experience in teaching and adaptation of foreign students. The concepts and projects to attract foreign students to the Russian Federation also have been described in detail. Special attention to two projects “5–100” and “Export of Russian education” has been paid. The Federal Agency for the Commonwealth of Independent States Affairs, Compatriots Living Abroad, and International Humanitarian Cooperation (Rossotrudnichestvo) as one of the main institutions in the export of Russian education has been designated. The measures to attract foreign students to Russian universities have been proposed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.299
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it